From 20,000 genes to 2 targets
Your program should invest in
We build program-specific AI solutions that help Biopharma R&D teams identify
targets they can confidently pursue.
targets they can confidently pursue.
From 20,000 genes to 2 targets
90+
Partners in Biopharma R&D
40+
Programs Advanced Beyond IND
10+
Years of Program Specific AI Solutions
Problem
Every Target Decision is a $2M Bet
Teams need to evaluate 10–20 competing targets simultaneously across modalities,
with no reliable framework.
20,000 Genes. 1 Validation Budget
Teams rely on anecdotal evidence and gut instinct to decide which 5–10 targets move into validation.
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Silo-ed Evaluation. Missed signals.
Teams evaluate candidates against different biological contexts, with no framework to rank them against each other.
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High Costs for Wrong Prioritization
Wrong target in validation mean 18 months and upwards of $2M committed to the wrong bet. This is a resource allocation mistake at the program-level
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Our approach
Purpose-Built Target Validation Stack
You bring your differentiated therapeutic thesis and proprietary data. Elucidata co-builds a program-specific target decision system that connects evidence & surfaces targets your team can act on.
Step 01 · Curate
Build The Evidence Base for Target Validation
We harmonize your proprietary omics, assay, and experimental data, connect it to curated evidence from 20+ public sources, and run quality checks before it enters the graph, turning 20,000 genes into an evidence-linked target landscape.
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Step 02 · shortlist
Narrow Targets with Purpose-Built Knowledge Graphs
The knowledge graph is built around your program context and not just a broad disease label. It connects evidence across genetics, transcriptomics, proteomics, and disease mechanisms for every target, and helps filter generic associations into program-relevant targets.
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Step 03 · score
Score targets by evidence strength & program fit
Each target is ranked using a custom scoring framework aligned to your differentiated therapeutic thesis. Our in-silico perturbation model stress-tests hits across unscreened, disease-relevant contexts to show which signals are likely to hold up.
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Step 04 · Decide
Select the 2 Targets worth Backing
Your team gets a Target Dashboard with evidence grades for each target across genetics, multi-modal omics, disease biology, druggability, and confidence level. Every ranked candidate includes mechanistic rationale and source-linked evidence, helping your team decide which 2 targets are worth investing in.
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Technology
Polly: The Agentic Stack for Target Validation
Polly ingests your proprietary data and public biomedical evidence, connects it through a knowledge graph, scores candidates across 14 dimensions, and delivers a ranked, decision-ready target list your team can defend.
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partner with us
We are a Full-Stack Target Validation Partner
Data Partner
AI-ready multi-modal data delivered with quality & speed.
We harmonize multi-modal R&D data across proprietary and public sources, delivering quality-checked data products at high volume. These data products are ready for analysis apps, knowledge graphs, and AI workflows.
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Case Study
Bioinformatics Partner
We build the methodologies your multi-omics data needs.
From spatial omics pipelines to specialized screening methodologies and single-cell workflows, we develop scaleable analysis frameworks tailored to each program’s biology not generic pipelines repurposed for your data.
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Case study
Infrastructure Partner
We build and run the platform your discovery team works on.
We build the AI and data infrastructure behind target discovery workflows. From custom knowledge graphs, evidence retrieval to co-scientists, agentic workflows, all deployed on Polly or your infrastructure.
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Case Study
Talk to our Expert
Why Elucidata
Better Target Bets Not Bigger Target Lists
LLMs summarize papers. Generic AI Tools surface associations. We build knowledge graphs & models that show the mechanistic trail behind every target recommendation.
01
Built around your differentiated biology
Generic KG platforms score targets against public disease ontologies. We build the knowledge graph around your biological hypothesis and program-context.
02
Multi-modal evidence convergence
We traverse genetics, transcriptomics, proteomics, and disease mechanisms in one pass per target. One strong signal does not mask missing evidence elsewhere.
03
A decision dashboard, not a discovery tool
Your team gets a ranked target shortlist with confidence levels, mechanistic rationale, and source links to decide what moves into validation. Used by top-10 Pharma teams to support validation decisions.
04
Evidence weighted by confidence
Human genetic, clinical, animal model, and computational evidence are not weighted equally. We distinguish cytotoxicity from mechanism, and association from causation.
Customer Stories
Accelerating AML Target-indication Assessment With Advanced Knowledge Graphs
A Massachusetts-based therapeutics company sought to accelerate AML target-indication assessment using differentiation therapy, a novel approach that transforms malignant cells into healthy functional ones.
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Data-Centric Cross-Species Target Discovery with Polly KG
A Boston-based biotech focused on immune and metabolic diseases was hampered by siloed non-model datasets; our scalable ETL pipeline and Base-KG unified them into one AI-ready foundation from day one.
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Identified and Validated Novel AML Targets 4X Faster With Multi-Modal Evidence
In collaboration with Elucidata, a US-based therapeutics company identified a novel Acute Myeloid Leukemia target in just 6 months. It has advanced to clinical trials, offering hope to 100k+ patients.
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Pharma Company Achieves 4x Faster Target ID for Inflammatory Disease
A pharmaceutical company based in Boston aimed to speed up their target discovery and validation process for inflammatory disease using single-cell RNA-seq data.
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Recent Publications
Optimization of Experiment Design for Mass Spectrometric Isotopic Labeling Kinetics
Multi-Agent AI System for High Quality Metadata Curation at Scale
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The decision is a $2M bet.
The conversation is free.
The conversation is free.
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